Study on Control of Facial Expressions of Face Robot and Their Informatic Characterisitics

人脸机器人面部表情控制及其信息特征研究

基本信息

批准号：
05452172
负责人：
HARA Fumio
金额：
$ 4.74万
依托单位：
Science University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (B)
财政年份：
1993
资助国家：
日本
起止时间：
1993 至 1994
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-05452172/
关键词：
Face robot 6 basic facial expressions Action units Real-time control Dynamic facial expressions Real-time measurement of motions in eye, eye brow and mouth Real-time recognition of facial expressions 動的表情認識基本表情表情制御特徴点アクションユニット

项目摘要

(1) The face robot consitutes of a head-frame structure, 18 facial muscle FMA actuators, silicone-rubber face skin, eyes, mouth, nose and neck structure and has 18 degree-of-freedom to mimic the movement of human face motion. The size of the face robot is 20% larger tahn that of normal human face. The motion of face components for expressiong 6 basic facial expressions are determined according to the kind and strength of Action Units used in psychology and control algorithm for the facial expressions has been established.(2) The 6 basic facial expressions displayd on the face robot were evaluated by visual test and obtained about 90% correct expression except for "Fear" expression.(3) Small size air-cylinder-piston type actuator was developed for real-time motion of facial expression and 18 of this actuators were implemented into the face robot and control algorithm was established by using a feedback control in each actuator for realizing a real-time motion of facial expressions on the face robot.(4) By using the transputer system and 2 CCD cameras, the real-time measurement of motions in eyes, eye brows and mouth was successfully performed. The time needed for one dynamic facial image measurement was about 100 ms which is sufficently short for our dynamic recognition of facial expressions.(5) The dynamic facial image data obtained by the transputer system were applied to the neural network trained by typical facial expressions and recognition tests were undertaken to evaluate the performance of facial expressions of the face robot and obtained a rather high rate (about 80% correct ratio).(6) Some of future works will be to investigate the interactive characteristics of psychological information exchange between human and face robot by using facial expressions.

（1）面部机器人的头部框架结构，18个面部肌肉FMA执行器，硅胶橡胶的脸部皮肤，眼睛，嘴巴，鼻子，鼻子和颈部结构，并具有18度自由度，以模仿人脸运动的运动。面部机器人的大小是正常人脸的20％大的tahn。已经确定了表达式的面部成分6基本的面部表情，根据心理学和控制算法在面部表情中使用的动作和控制算法的种类和强度确定。（2）通过视觉测试进行了6个基本表情显示在面部机器人上显示的6个基本表情，并通过视觉测试进行了约90％的表达方式，表达了90％的表达和“恐惧”的表达。通过在面部机器人上使用每个执行器中的反馈控制来实现面部表情的实时运动来确定该执行器的面部机器人。（4）通过使用Transputer System和2个CCD摄像机，眼睛，眼睛眉毛和嘴成功执行了对运动的实时测量。一个动态的面部图像测量所需的时间约为100毫秒，这是我们对面部表情的动态识别的足够短的时间。（5）将传递器系统获得的动态面部图像数据应用于通过典型的面部表情训练的神经网络，并进行了典型的面部表情和识别测试，以评估某些脸部表达式的效果，并获得了一些较高的率（并获得了一个较高的率）（未来的率）（50％）（在50％的范围内）。通过使用面部表情来研究人与面部机器人之间心理信息交流的互动特征。